Conventional travel demand and other planning data sources provided very limited coverage on non-motorized modes such as biking and pedestrian. Crowd-sourcing approach has the potential to collect more up-to-date data for these modes with minimal costs and at a continuous basis. However, such data is mostly self-reported and lacks a unified format and standard, which compromises the data quality. More advanced data processing, cleansing, and integration methods are needed to make such data sources useful and valuable. This study investigated a set of biking incidents data collected in the Washington D.C. metropolitan area to explore such potentials.